#import libraries
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
import plotly.io as pio
pio.templates.default = "plotly_white"
#loading Dataset
data = pd.read_csv(r'C:\Users\Venkatesh\Downloads\t20-world-cup-22.csv')
print(data.head())
venue team1 team2 stage toss winner \ 0 SCG New Zealand Australia Super 12 Australia 1 Optus Stadium Afghanistan England Super 12 England 2 Blundstone Arena Ireland Sri lanka Super 12 Ireland 3 MCG Pakistan India Super 12 India 4 Blundstone Arena Bangladesh Netherlands Super 12 Netherlands toss decision first innings score first innings wickets \ 0 Field 200.0 3.0 1 Field 112.0 10.0 2 Bat 128.0 8.0 3 Field 159.0 8.0 4 Field 144.0 8.0 second innings score second innings wickets winner won by \ 0 111.0 10.0 New Zealand Runs 1 113.0 5.0 England Wickets 2 133.0 1.0 Sri lanka Wickets 3 160.0 6.0 India Wickets 4 135.0 10.0 Bangladesh Runs player of the match top scorer highest score best bowler \ 0 Devon Conway Devon Conway 92.0 Tim Southee 1 Sam Curran Ibrahim Zadran 32.0 Sam Curran 2 Kusal Mendis Kusal Mendis 68.0 Maheesh Theekshana 3 Virat Kohli Virat Kohli 82.0 Hardik Pandya 4 Taskin Ahmed Colin Ackermann 62.0 Taskin Ahmed best bowling figure 0 3-6 1 5-10 2 2-19 3 3-30 4 4-25
# Checking Number of Matches Won by each teams
figure = px.bar(data,
x=data["winner"],
title="Number of Matches Won by teams in t20 World Cup 2022")
figure.show()
#England won most of the matches including final
#Winning team by First vs Second batting
won_by = data["won by"].value_counts()
label = won_by.index
counts = won_by.values
fig = go.Figure(data=[go.Pie(labels=label, values=counts)])
fig.update_layout(title_text='Number of Matches Won By Runs Or Wickets')
fig.show()
#Batting first team has more percentange of win
#Looking at Toss decisions
toss = data["toss decision"].value_counts()
label = toss.index
counts = toss.values
colors = ['skyblue','yellow']
fig = go.Figure(data=[go.Pie(labels=label, values=counts)])
fig.update_layout(title_text='Toss Decisions in t20 World Cup 2022')
fig.update_traces(hoverinfo='label+percent', textinfo='value', textfont_size=30,
marker=dict(colors=colors, line=dict(color='black', width=3)))
fig.show()
#Most of the teams chose batting after winning toss
#Looking at Top Batsman
figure = px.bar(data,
x=data["top scorer"],
y = data["highest score"],
color = data["highest score"],
title="Top Scorers in t20 World Cup 2022")
figure.show()
#Virat kohli has most runs and Rilee Rossouw has highest run in single match
#Player of the match
figure = px.bar(data,
x = data["player of the match"],
color = data["player of the match"],
title="Player of the Match Awards in t20 World Cup 2022")
figure.show()
#Best bowler in the tournament
figure = px.bar(data,
x=data["best bowler"],
title="Best Bowlers in t20 World Cup 2022")
figure.show()
#Sam curran got player of the tournament award and having best bowling figures
#First innings vs Second innings
fig = go.Figure()
fig.add_trace(go.Bar(
x=data["venue"],
y=data["first innings score"],
name='First Innings Runs',
marker_color='green'
))
fig.add_trace(go.Bar(
x=data["venue"],
y=data["second innings score"],
name='Second Innings Runs',
marker_color='red'
))
fig.update_layout(barmode='group',
xaxis_tickangle=-45,
title="Best Stadiums to Bat First or Chase")
fig.show()
#SCG is the Best Stadium for Batting whereas other stadium doesnt have much difference
fig = go.Figure()
fig.add_trace(go.Bar(
x=data["venue"],
y=data["first innings wickets"],
name='First Innings Wickets',
marker_color='green'
))
fig.add_trace(go.Bar(
x=data["venue"],
y=data["second innings wickets"],
name='Second Innings Wickets',
marker_color='red'
))
fig.update_layout(barmode='group',
xaxis_tickangle=-45,
title="Best Statiums to Bowl First or Defend")
fig.show()
#SCG Stadium is good to defend runs and Optus Stadium is good for Second innings batting team